Role Description You are the first person a new client has a real conversation with. You understand their data environment, their team structure, their actual friction — not their stated problem. You scope engagements around the named person with the named pain. No generic AI evaluations. No pilot programs designed to go nowhere. You stay involved through delivery, making sure what gets built matches what was promised — and that what was promised was the right thing to promise. This is a senior advisory role. You operate with significant autonomy, shape methodology, and influence how edisyl goes to market with its largest customers. What You'll Actually Do - Lead data strategy engagements with enterprise customers — assessing current state, defining a target architecture, developing phased roadmaps toward AI activation - Run executive-level workshops to align business objectives with data and AI investment priorities - Define data governance, quality, and readiness frameworks that help customers get value from edisyl faster - Partner with Forward-Deployed Engineers to translate strategic intent into executable implementation plans - Identify expansion opportunities by connecting latent data assets to new AI use cases - Codify methodology and contribute to edisyl's market positioning through thought leadership What Success Looks Like in Year One - You've led strategy engagements across multiple enterprise accounts and at least two have moved from assessment into active deployment. - You've built a data maturity framework and engagement model the team can run repeatedly — not just describe. - The clients you've worked with are asking for the next phase before the current one is done. - The measure isn't whether the strategy was elegant. It's whether something changed in the client's business because of it. Qualifications - 6–10 years combining data strategy with direct client or executive advisory exposure — senior engagement manager or principal-level at a data or management consulting firm, or director-or-above inside a large enterprise data org - You've run executive-facing workshops and translated ambiguous business needs into structured data requirements - Strong grasp of modern data architecture: data mesh, lakehouse, real-time vs. batch, governance frameworks - Experience in at least one priority vertical — financial services, insurance, or crypto/blockchain infrastructure — strongly preferred Requirements - Sharp diagnostic instincts. - Comfort with ambiguity. - Outcome orientation. - Strong opinions. Bonus (Genuinely Not Required) - Background at a firm known for forward-deployed or consultative advisory — McKinsey Data, Palantir, Databricks professional services, or similar - Experience working directly with a CEO or founder in a small-company or build-out context - Familiarity with blockchain data, DeFi, or institutional crypto infrastructure Compensation Competitive base salary, meaningful early-stage equity, and a variable component tied to the engagements you lead and the expansions you drive. We'll be transparent about the full picture in our first conversation. To Apply Complete the online application and include responses to: 1) why this role fits where you are in your career right now, and why you are the right person for it; and 2) one example of an enterprise data engagement where the stated problem wasn't the real problem — what you found, how you reframed it, and what happened next. No template. Just tell us the story.